1
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Dahmani Z, Scott AL, Vénien-Bryan C, Perahia D, Costa MG. MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search. J Chem Inf Model 2024; 64:5151-5160. [PMID: 38907694 PMCID: PMC11234365 DOI: 10.1021/acs.jcim.3c02007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 06/17/2024] [Accepted: 06/17/2024] [Indexed: 06/24/2024]
Abstract
Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.
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Affiliation(s)
- Zakaria
L. Dahmani
- School
of Medicine, Department of Computational and Systems Biology, University of Pittsburgh, 800 Murdoch I Bldg, 3420 Forbes Avenue, Pittsburgh, Pennsylvania 15260, United States
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
| | - Ana Ligia Scott
- CMCC,
Computational Biophysics and Biology, Universidade Federal do ABC, Avenida dos Estados 5001, São Paulo, Santo André 09210-580, Brazil
- Université
de Strasbourg—IGBMC—Departament de Biologie structurale
integrative, 1 rue Laurent
Fries BP, Illkirch 10142
67404, CEDEX, France
| | - Catherine Vénien-Bryan
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
| | - David Perahia
- Laboratoire
de Biologie et Pharmacologie Appliquée, UMR 8113, École
Normale Supérieure Paris-Saclay, Gif-sur-Yvette 91190, France
| | - Mauricio G.S Costa
- UMR
7590, CNRS, Museum National d’Histoire Naturelle, Institut
de Minéralogie, Physique des Matériaux et Cosmochimie,
IMPMC, Sorbonne Université, 4 place Jussieu, Paris 75005, France
- Laboratoire
de Biologie et Pharmacologie Appliquée, UMR 8113, École
Normale Supérieure Paris-Saclay, Gif-sur-Yvette 91190, France
- Programa de Computação Científica,
Vice-Presidência de Educação, Informação
e Comunicação, Fundação Oswaldo Cruz, Av.Brasil 4365, Residência
Oficial, Manguinhos, Rio de Janeiro 21040-900, Brazil
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2
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Zheng W, Liu X. Modeling and Simulation of the NMDA Receptor at Coarse-Grained and Atomistic Levels. Methods Mol Biol 2024; 2799:269-280. [PMID: 38727913 DOI: 10.1007/978-1-0716-3830-9_15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
N-Methyl-D-aspartate (NMDA) receptors are glutamate-gated excitatory channels that play essential roles in brain functions. While high-resolution structures were solved for an allosterically inhibited form of functional NMDA receptor, other key functional states (particularly the active open-channel state) have not yet been resolved at atomic resolutions. To decrypt the molecular mechanism of the NMDA receptor activation, structural modeling and simulation are instrumental in providing detailed information about the dynamics and energetics of the receptor in various functional states. In this chapter, we describe coarse-grained modeling of the NMDA receptor using an elastic network model and related modeling/analysis tools (e.g., normal mode analysis, flexibility and hotspot analysis, cryo-EM flexible fitting, and transition pathway modeling) based on available structures. Additionally, we show how to build an atomistic model of the active-state receptor with targeted molecular dynamics (MD) simulation and explore its energetics and dynamics with conventional MD simulation. Taken together, these modeling and simulation can offer rich structural and dynamic information which will guide experimental studies of the activation of this key receptor.
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Affiliation(s)
- Wenjun Zheng
- Department of Physics, State University of New York at Buffalo, Buffalo, NY, USA.
| | - Xing Liu
- Department of Physics, State University of New York at Buffalo, Buffalo, NY, USA
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3
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Dasgupta B, Tiwari SP. Explicit versus implicit consideration of binding partners in protein-protein complex to elucidate intrinsic dynamics. Biophys Rev 2022; 14:1379-1392. [PMID: 36659985 PMCID: PMC9842844 DOI: 10.1007/s12551-022-01026-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/27/2022] [Indexed: 12/23/2022] Open
Abstract
The binding of many proteins to their protein partners is tightly regulated via control of their relative intrinsic dynamics during the binding process, a phenomenon which can in turn be modulated. Therefore, investigating the intrinsic dynamics of proteins is necessary to understand function in a comprehensive way. By intrinsic dynamics herein, we principally refer to the vibrational signature of a protein molecule popularly obtained from normal modes or essential modes. For normal modes, one often considers that the molecule under investigation is a collection of springs in a solvent-free or implicit-solvent medium. In the context of a protein-binding partner, the analysis of vibration of the target protein is often complicated due to molecular interaction within the complex. Generally, it is assumed that the isolated bound conformation of the target protein captures the implicit effect of the binding partner on the intrinsic dynamics, therefore suggesting that any influence of the partner molecule is also already integrated. Such an assumption allows large-scale studies of the conservation of protein flexibility. However, in cases where a partner protein directly influences the vibration of the target via critical contacts at the protein-protein interface, the above assumption falls short of providing a detailed view. In this review article, we discuss the implications of considering the dynamics of a protein in a protein-protein complex, as modelled implicitly and explicitly with methods dependent on elastic network models. We further propose how such an explicit consideration can be applied to understand critical protein-protein contacts that can be targeted in future studies.
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Affiliation(s)
- Bhaskar Dasgupta
- Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-Ku, Tokyo, 153-8904 Japan
| | - Sandhya P. Tiwari
- Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima City, 1-3-1 Kagamiyama, Hiroshima, 739-8526 Japan
- Present Address: Institute of Protein Research, Osaka University, 3-2 Yamadaoka, Suita-Shi, Osaka, 565-0871 Japan
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4
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Zhu Z, Deng Z, Wang Q, Wang Y, Zhang D, Xu R, Guo L, Wen H. Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design. Front Pharmacol 2022; 13:939555. [PMID: 35837274 PMCID: PMC9275593 DOI: 10.3389/fphar.2022.939555] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 06/07/2022] [Indexed: 11/13/2022] Open
Abstract
Ion channels are expressed in almost all living cells, controlling the in-and-out communications, making them ideal drug targets, especially for central nervous system diseases. However, owing to their dynamic nature and the presence of a membrane environment, ion channels remain difficult targets for the past decades. Recent advancement in cryo-electron microscopy and computational methods has shed light on this issue. An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how simulation and machine learning-based methods fundamentally changed the ion channel-related drug design at different levels, as well as the emerging trends in the field.
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Affiliation(s)
- Zhengdan Zhu
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing Institute of Big Data Research, Beijing, China
| | - Zhenfeng Deng
- DP Technology, Beijing, China
- School of Pharmaceutical Sciences, Peking University, Beijing, China
| | | | | | - Duo Zhang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- DP Technology, Beijing, China
| | - Ruihan Xu
- DP Technology, Beijing, China
- National Engineering Research Center of Visual Technology, Peking University, Beijing, China
| | | | - Han Wen
- DP Technology, Beijing, China
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5
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Exploring cryo-electron microscopy with molecular dynamics. Biochem Soc Trans 2022; 50:569-581. [PMID: 35212361 DOI: 10.1042/bst20210485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/31/2022] [Accepted: 02/02/2022] [Indexed: 11/17/2022]
Abstract
Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.
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6
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Laine E, Grudinin S. HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps. J Phys Chem B 2021; 125:2577-2588. [PMID: 33687221 DOI: 10.1021/acs.jpcb.0c11633] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches. We present HOPMA, a novel method to predict protein functional states and transitions by using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures. The method is computationally efficient and available at https://github.com/elolaine/HOPMA and https://team.inria.fr/nano-d/software/nolb-normal-modes.
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Affiliation(s)
- Elodie Laine
- CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005 Paris, France
| | - Sergei Grudinin
- CNRS, Inria, Grenoble INP, LJK, Univ. Grenoble Alpes, 38000 Grenoble, France
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7
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Jernigan RL, Sankar K, Jia K, Faraggi E, Kloczkowski A. Computational Ways to Enhance Protein Inhibitor Design. Front Mol Biosci 2021; 7:607323. [PMID: 33614705 PMCID: PMC7886686 DOI: 10.3389/fmolb.2020.607323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 12/08/2020] [Indexed: 11/22/2022] Open
Abstract
Two new computational approaches are described to aid in the design of new peptide-based drugs by evaluating ensembles of protein structures from their dynamics and through the assessing of structures using empirical contact potential. These approaches build on the concept that conformational variability can aid in the binding process and, for disordered proteins, can even facilitate the binding of more diverse ligands. This latter consideration indicates that such a design process should be less restrictive so that multiple inhibitors might be effective. The example chosen here focuses on proteins/peptides that bind to hemagglutinin (HA) to block the large-scale conformational change for activation. Variability in the conformations is considered from sets of experimental structures, or as an alternative, from their simple computed dynamics; the set of designe peptides/small proteins from the David Baker lab designed to bind to hemagglutinin, is the large set considered and is assessed with the new empirical contact potentials.
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Affiliation(s)
- Robert L. Jernigan
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, United States
| | - Kannan Sankar
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, United States
| | - Kejue Jia
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA, United States
| | - Eshel Faraggi
- Research and Information Systems, LLC, Indianapolis, IN, United States
- Department of Physics, Indiana University Purdue University Indianapolis, Indianapolis, IN, United States
| | - Andrzej Kloczkowski
- Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, Columbus, OH, United States
- Department of Pediatrics, The Ohio State University, Columbus, OH, United States
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8
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Seffernick JT, Lindert S. Hybrid methods for combined experimental and computational determination of protein structure. J Chem Phys 2020; 153:240901. [PMID: 33380110 PMCID: PMC7773420 DOI: 10.1063/5.0026025] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/10/2020] [Indexed: 02/04/2023] Open
Abstract
Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.
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Affiliation(s)
- Justin T. Seffernick
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
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9
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Grudinin S, Laine E, Hoffmann A. Predicting Protein Functional Motions: an Old Recipe with a New Twist. Biophys J 2020; 118:2513-2525. [PMID: 32330413 DOI: 10.1016/j.bpj.2020.03.020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 03/09/2020] [Accepted: 03/18/2020] [Indexed: 01/21/2023] Open
Abstract
Large macromolecules, including proteins and their complexes, very often adopt multiple conformations. Some of them can be seen experimentally, for example with x-ray crystallography or cryo-electron microscopy. This structural heterogeneity is not occasional and is frequently linked with specific biological function. Thus, the accurate description of macromolecular conformational transitions is crucial for understanding fundamental mechanisms of life's machinery. We report on a real-time method to predict such transitions by extrapolating from instantaneous eigen motions, computed using the normal mode analysis, to a series of twists. We demonstrate the applicability of our approach to the prediction of a wide range of motions, including large collective opening-closing transitions and conformational changes induced by partner binding. We also highlight particularly difficult cases of very small transitions between crystal and solution structures. Our method guarantees preservation of the protein structure during the transition and allows accessing conformations that are unreachable with classical normal mode analysis. We provide practical solutions to describe localized motions with a few low-frequency modes and to relax some geometrical constraints along the predicted transitions. This work opens the way to the systematic description of protein motions, whatever their degree of collectivity. Our method is freely available as a part of the NOn-Linear rigid Block (NOLB) package.
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Affiliation(s)
- Sergei Grudinin
- University Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble, France.
| | - Elodie Laine
- Sorbonne Université, CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Paris, France
| | - Alexandre Hoffmann
- University Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble, France
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10
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Alnabati E, Kihara D. Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps. Molecules 2019; 25:molecules25010082. [PMID: 31878333 PMCID: PMC6982917 DOI: 10.3390/molecules25010082] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 12/20/2019] [Accepted: 12/20/2019] [Indexed: 01/16/2023] Open
Abstract
Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting, flexible fitting, and de novo modeling methods. It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. Here, we review these different categories of macromolecule structure modeling methods and discuss their advances over time.
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Affiliation(s)
- Eman Alnabati
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
- Correspondence:
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11
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Malhotra S, Träger S, Dal Peraro M, Topf M. Modelling structures in cryo-EM maps. Curr Opin Struct Biol 2019; 58:105-114. [PMID: 31394387 DOI: 10.1016/j.sbi.2019.05.024] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2019] [Revised: 05/23/2019] [Accepted: 05/25/2019] [Indexed: 12/20/2022]
Abstract
Recent advances in structure determination of sub-cellular structures using cryo-electron microscopy and tomography have enabled us to understand their architecture in a more detailed manner and gain insight into their function. The choice of approach to use for atomic model building, fitting, refinement and validation in the 3D map resulting from these experiments depends primarily on the resolution of the map and the prior information on the corresponding model. Here, we survey some of such methods and approaches and highlight their uses in specific recent examples.
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Affiliation(s)
- Sony Malhotra
- Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom
| | - Sylvain Träger
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Matteo Dal Peraro
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Maya Topf
- Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom.
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12
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Kim DN, Moriarty NW, Kirmizialtin S, Afonine PV, Poon B, Sobolev OV, Adams PD, Sanbonmatsu K. Cryo_fit: Democratization of flexible fitting for cryo-EM. J Struct Biol 2019; 208:1-6. [PMID: 31279069 PMCID: PMC7112765 DOI: 10.1016/j.jsb.2019.05.012] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 05/31/2019] [Indexed: 12/18/2022]
Abstract
Cryo-electron microscopy (cryo-EM) is becoming a method of choice for describing native conformations of biomolecular complexes at high resolution. The rapid growth of cryo-EM in recent years has created a high demand for automated solutions, both in hardware and software. Flexible fitting of atomic models to three-dimensional (3D) cryo-EM reconstructions by molecular dynamics (MD) simulation is a popular technique but often requires technical expertise in computer simulation. This work introduces cryo_fit, a package for the automatic flexible fitting of atomic models in cryo-EM maps using MD simulation. The package is integrated with the Phenix software suite. The module was designed to automate the multiple steps of MD simulation in a reproducible manner, as well as facilitate refinement and validation through Phenix. Through the use of cryo_fit, scientists with little experience in MD simulation can produce high quality atomic models automatically and better exploit the potential of cryo-EM.
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Affiliation(s)
- Doo Nam Kim
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Nigel W Moriarty
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Serdal Kirmizialtin
- Chemistry Program, Science Division, New York University, Abu Dhabi, United Arab Emirates
| | - Pavel V Afonine
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Billy Poon
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Oleg V Sobolev
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA
| | - Paul D Adams
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA, USA; Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA
| | - Karissa Sanbonmatsu
- Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM, USA; New Mexico Consortium, Los Alamos, NM, USA.
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13
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Bauer JA, Pavlović J, Bauerová-Hlinková V. Normal Mode Analysis as a Routine Part of a Structural Investigation. Molecules 2019; 24:E3293. [PMID: 31510014 PMCID: PMC6767145 DOI: 10.3390/molecules24183293] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 08/30/2019] [Accepted: 08/30/2019] [Indexed: 12/13/2022] Open
Abstract
Normal mode analysis (NMA) is a technique that can be used to describe the flexible states accessible to a protein about an equilibrium position. These states have been shown repeatedly to have functional significance. NMA is probably the least computationally expensive method for studying the dynamics of macromolecules, and advances in computer technology and algorithms for calculating normal modes over the last 20 years have made it nearly trivial for all but the largest systems. Despite this, it is still uncommon for NMA to be used as a component of the analysis of a structural study. In this review, we will describe NMA, outline its advantages and limitations, explain what can and cannot be learned from it, and address some criticisms and concerns that have been voiced about it. We will then review the most commonly used techniques for reducing the computational cost of this method and identify the web services making use of these methods. We will illustrate several of their possible uses with recent examples from the literature. We conclude by recommending that NMA become one of the standard tools employed in any structural study.
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Affiliation(s)
- Jacob A Bauer
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava, Slovakia.
| | - Jelena Pavlović
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava, Slovakia
| | - Vladena Bauerová-Hlinková
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská cesta 21, 845 51 Bratislava, Slovakia
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14
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Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning. Nat Methods 2019; 16:911-917. [PMID: 31358979 PMCID: PMC6717539 DOI: 10.1038/s41592-019-0500-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 06/24/2019] [Indexed: 02/05/2023]
Abstract
An increasing number of protein structures have been solved by cryo-electron microscopy (cryo-EM). Although structures determined at near-atomic resolution are now routinely reported, many density maps are still determined at an intermediate resolution, where extracting structure information is still a challenge. We have developed a computational method, Emap2sec, which identifies the secondary structures of proteins (α helices, β sheets, and other structures) in an EM map of 5 to 10 Å resolution. Emap2sec uses a 3D deep convolutional neural network to assign secondary structure to each grid point in an EM map. We tested Emap2sec on 6.0 and 10.0 Å resolution EM maps simulated from 34 structures, as well as on 43 maps determined experimentally at 5.0 to 9.5 Å resolution. Emap2sec was able to clearly identify the secondary structures in many maps tested, and showed substantially better performance than existing methods.
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15
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Bonomi M, Vendruscolo M. Determination of protein structural ensembles using cryo-electron microscopy. Curr Opin Struct Biol 2019; 56:37-45. [DOI: 10.1016/j.sbi.2018.10.006] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 10/24/2018] [Accepted: 10/26/2018] [Indexed: 10/27/2022]
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16
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Simultaneous Determination of Protein Structure and Dynamics Using Cryo-Electron Microscopy. Biophys J 2019; 114:1604-1613. [PMID: 29642030 PMCID: PMC5954442 DOI: 10.1016/j.bpj.2018.02.028] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 02/05/2018] [Accepted: 02/20/2018] [Indexed: 11/21/2022] Open
Abstract
Cryo-electron microscopy is rapidly emerging as a powerful technique to determine the structures of complex macromolecular systems elusive to other techniques. Because many of these systems are highly dynamical, characterizing their movements is also a crucial step to unravel their biological functions. To achieve this goal, we report an integrative modeling approach to simultaneously determine structure and dynamics of macromolecular systems from cryo-electron microscopy density maps. By quantifying the level of noise in the data and dealing with their ensemble-averaged nature, this approach enables the integration of multiple sources of information to model ensembles of structures and infer their populations. We illustrate the method by characterizing structure and dynamics of the integral membrane receptor STRA6, thus providing insights into the mechanisms by which it interacts with retinol binding protein and translocates retinol across the membrane.
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Bonomi M, Hanot S, Greenberg CH, Sali A, Nilges M, Vendruscolo M, Pellarin R. Bayesian Weighing of Electron Cryo-Microscopy Data for Integrative Structural Modeling. Structure 2018; 27:175-188.e6. [PMID: 30393052 DOI: 10.1016/j.str.2018.09.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 08/07/2018] [Accepted: 09/19/2018] [Indexed: 10/28/2022]
Abstract
Cryo-electron microscopy (cryo-EM) has become a mainstream technique for determining the structures of complex biological systems. However, accurate integrative structural modeling has been hampered by the challenges in objectively weighing cryo-EM data against other sources of information due to the presence of random and systematic errors, as well as correlations, in the data. To address these challenges, we introduce a Bayesian scoring function that efficiently and accurately ranks alternative structural models of a macromolecular system based on their consistency with a cryo-EM density map as well as other experimental and prior information. The accuracy of this approach is benchmarked using complexes of known structure and illustrated in three applications: the structural determination of the GroEL/GroES, RNA polymerase II, and exosome complexes. The approach is implemented in the open-source Integrative Modeling Platform (http://integrativemodeling.org), thus enabling integrative structure determination by combining cryo-EM data with other sources of information.
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Affiliation(s)
| | - Samuel Hanot
- Institut Pasteur, Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, CNRS UMR 3528, C3BI USR 3756 CNRS & IP, Paris, France
| | - Charles H Greenberg
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Sciences, and California Institute for Quantitative Biomedical Sciences, University of California, San Francisco, CA 94158, USA
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Sciences, and California Institute for Quantitative Biomedical Sciences, University of California, San Francisco, CA 94158, USA
| | - Michael Nilges
- Institut Pasteur, Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, CNRS UMR 3528, C3BI USR 3756 CNRS & IP, Paris, France
| | | | - Riccardo Pellarin
- Institut Pasteur, Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, CNRS UMR 3528, C3BI USR 3756 CNRS & IP, Paris, France.
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18
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Kovacs JA, Galkin VE, Wriggers W. Accurate flexible refinement of atomic models against medium-resolution cryo-EM maps using damped dynamics. BMC STRUCTURAL BIOLOGY 2018; 18:12. [PMID: 30219048 PMCID: PMC6139150 DOI: 10.1186/s12900-018-0089-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 08/02/2018] [Indexed: 12/30/2022]
Abstract
BACKGROUND Dramatic progress has recently been made in cryo-electron microscopy technologies, which now make possible the reconstruction of a growing number of biomolecular structures to near-atomic resolution. However, the need persists for fitting and refinement approaches that address those cases that require modeling assistance. METHODS In this paper, we describe algorithms to optimize the performance of such medium-resolution refinement methods. These algorithms aim to automatically optimize the parameters that define the density shape of the flexibly fitted model, as well as the time-dependent damper cutoff distance. Atomic distance constraints can be prescribed for cases where extra containment of parts of the structure is helpful, such as in regions where the density map is poorly defined. Also, we propose a simple stopping criterion that estimates the probable onset of overfitting during the simulation. RESULTS The new set of algorithms produce more accurate fitting and refinement results, and yield a faster rate of convergence of the trajectory toward the fitted conformation. The latter is also more reliable due to the overfitting warning provided to the user. CONCLUSIONS The algorithms described here were implemented in the new Damped-Dynamics Flexible Fitting simulation tool "DDforge" in the Situs package.
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Affiliation(s)
- Julio A Kovacs
- Department of Mechanical and Aerospace Engineering, Old Dominion University, Norfolk, VA, USA
| | - Vitold E Galkin
- Department of Physiological Sciences, Eastern Virginia Medical School, Norfolk, VA, USA
| | - Willy Wriggers
- Department of Mechanical and Aerospace Engineering, Old Dominion University, Norfolk, VA, USA.
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19
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Tekpinar M. Flexible fitting to cryo-electron microscopy maps with coarse-grained elastic network models. MOLECULAR SIMULATION 2018. [DOI: 10.1080/08927022.2018.1431835] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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20
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Zhu L, Petrlova J, Gysbers P, Hebert H, Wallin S, Jegerschöld C, Lagerstedt JO. Structures of apolipoprotein A-I in high density lipoprotein generated by electron microscopy and biased simulations. Biochim Biophys Acta Gen Subj 2017; 1861:2726-2738. [DOI: 10.1016/j.bbagen.2017.07.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 07/18/2017] [Accepted: 07/24/2017] [Indexed: 10/19/2022]
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21
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Zheng W, Sachs F. Investigating the structural dynamics of the PIEZO1 channel activation and inactivation by coarse-grained modeling. Proteins 2017; 85:2198-2208. [PMID: 28905417 DOI: 10.1002/prot.25384] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 08/22/2017] [Accepted: 09/10/2017] [Indexed: 01/07/2023]
Abstract
The PIEZO channels, a family of mechanosensitive channels in vertebrates, feature a fast activation by mechanical stimuli (eg, membrane tension) followed by a slower inactivation. Although a medium-resolution structure of the trimeric form of PIEZO1 was solved by cryo-electron microscopy (cryo-EM), key structural changes responsible for the channel activation and inactivation are still unknown. Toward decrypting the structural mechanism of the PIEZO1 activation and inactivation, we performed systematic coarse-grained modeling using an elastic network model and related modeling/analysis tools (ie, normal mode analysis, flexibility and hotspot analysis, correlation analysis, and cryo-EM-based hybrid modeling and flexible fitting). We identified four key motional modes that may drive the tension-induced activation and inactivation, with fast and slow relaxation time, respectively. These modes allosterically couple the lateral and vertical motions of the peripheral domains to the opening and closing of the intra-cellular vestibule, enabling external mechanical forces to trigger, and regulate the activation/inactivation transitions. We also calculated domain-specific flexibility profiles, and predicted hotspot residues at key domain-domain interfaces and hinges. Our results offer unprecedented structural and dynamic information, which is consistent with the literature on mutational and functional studies of the PIEZO channels, and will guide future studies of this important family of mechanosensitive channels.
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Affiliation(s)
- Wenjun Zheng
- Department of Physics, State University of New York at Buffalo, Buffalo, New York
| | - Frederick Sachs
- Department of Physiology and Biophysics, State University of New York at Buffalo, Buffalo, New York
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22
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Zheng W, Wen H, Iacobucci GJ, Popescu GK. Probing the Structural Dynamics of the NMDA Receptor Activation by Coarse-Grained Modeling. Biophys J 2017. [PMID: 28636915 DOI: 10.1016/j.bpj.2017.04.043] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
N-Methyl-D-aspartate (NMDA) receptors are glutamate-gated excitatory channels that play essential roles in brain functions. High-resolution structures have been solved for an allosterically inhibited and agonist-bound form of a functional NMDA receptor; however, other key functional states (particularly the active open-channel state) were only resolved at moderate resolutions by cryo-electron microscopy (cryo-EM). To decrypt the mechanism of the NMDA receptor activation, structural modeling is essential to provide presently missing information about structural dynamics. We performed systematic coarse-grained modeling using an elastic network model and related modeling/analysis tools (e.g., normal mode analysis, flexibility and hotspot analysis, cryo-EM flexible fitting, and transition pathway modeling) based on an active-state cryo-EM map. We observed extensive conformational changes that allosterically couple the extracellular regulatory and agonist-binding domains to the pore-forming trans-membrane domain (TMD), and validated these, to our knowledge, new observations against known mutational and functional studies. Our results predict two key modes of collective motions featuring shearing/twisting of the extracellular domains relative to the TMD, reveal subunit-specific flexibility profiles, and identify functional hotspot residues at key domain-domain interfaces. Finally, by examining the conformational transition pathway between the allosterically inhibited form and the active form, we predict a discrete sequence of domain motions, which propagate from the extracellular domains to the TMD. In summary, our results offer rich structural and dynamic information, which is consistent with the literature on structure-function relationships in NMDA receptors, and will guide in-depth studies on the activation dynamics of this important neurotransmitter receptor.
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Affiliation(s)
- Wenjun Zheng
- Department of Physics, State University of New York at Buffalo, Buffalo, New York.
| | - Han Wen
- Department of Physics, State University of New York at Buffalo, Buffalo, New York
| | - Gary J Iacobucci
- Department of Biochemistry, State University of New York at Buffalo, Buffalo, New York
| | - Gabriela K Popescu
- Department of Biochemistry, State University of New York at Buffalo, Buffalo, New York
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23
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Dou H, Burrows DW, Baker ML, Ju T. Flexible Fitting of Atomic Models into Cryo-EM Density Maps Guided by Helix Correspondences. Biophys J 2017. [PMID: 28636906 DOI: 10.1016/j.bpj.2017.04.054] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Although electron cryo-microscopy (cryo-EM) has recently achieved resolutions of better than 3 Å, at which point molecular modeling can be done directly from the density map, analysis and annotation of a cryo-EM density map still primarily rely on fitting atomic or homology models to the density map. In this article, we present, to our knowledge, a new method for flexible fitting of known or modeled protein structures into cryo-EM density maps. Unlike existing methods that are guided by local density gradients, our method is guided by correspondences between the α-helices in the density map and model, and does not require an initial rigid-body fitting step. Compared with current methods on both simulated and experimental density maps, our method not only achieves greater accuracy for proteins with large deformations but also runs as fast or faster than many of the other flexible fitting routines.
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Affiliation(s)
- Hang Dou
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri.
| | - Derek W Burrows
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri
| | - Matthew L Baker
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas
| | - Tao Ju
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri
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24
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Peng J, Zhang Z. Unraveling low-resolution structural data of large biomolecules by constructing atomic models with experiment-targeted parallel cascade selection simulations. Sci Rep 2016; 6:29360. [PMID: 27377017 PMCID: PMC4932515 DOI: 10.1038/srep29360] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 06/17/2016] [Indexed: 11/09/2022] Open
Abstract
Various low-resolution experimental techniques have gained more and more popularity in obtaining structural information of large biomolecules. In order to interpret the low-resolution structural data properly, one may need to construct an atomic model of the biomolecule by fitting the data using computer simulations. Here we develop, to our knowledge, a new computational tool for such integrative modeling by taking the advantage of an efficient sampling technique called parallel cascade selection (PaCS) simulation. For given low-resolution structural data, this PaCS-Fit method converts it into a scoring function. After an initial simulation starting from a known structure of the biomolecule, the scoring function is used to pick conformations for next cycle of multiple independent simulations. By this iterative screening-after-sampling strategy, the biomolecule may be driven towards a conformation that fits well with the low-resolution data. Our method has been validated using three proteins with small-angle X-ray scattering data and two proteins with electron microscopy data. In all benchmark tests, high-quality atomic models, with generally 1-3 Å from the target structures, are obtained. Since our tool does not need to add any biasing potential in the simulations to deform the structure, any type of low-resolution data can be implemented conveniently.
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Affiliation(s)
- Junhui Peng
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China
| | - Zhiyong Zhang
- Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China
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25
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Kmiecik S, Gront D, Kolinski M, Wieteska L, Dawid AE, Kolinski A. Coarse-Grained Protein Models and Their Applications. Chem Rev 2016; 116:7898-936. [DOI: 10.1021/acs.chemrev.6b00163] [Citation(s) in RCA: 555] [Impact Index Per Article: 69.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Sebastian Kmiecik
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Dominik Gront
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Michal Kolinski
- Bioinformatics
Laboratory, Mossakowski Medical Research Center of the Polish Academy of Sciences, Pawinskiego 5, 02-106 Warsaw, Poland
| | - Lukasz Wieteska
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
- Department
of Medical Biochemistry, Medical University of Lodz, Mazowiecka 6/8, 92-215 Lodz, Poland
| | | | - Andrzej Kolinski
- Faculty
of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
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26
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Zheng W. Toward decrypting the allosteric mechanism of the ryanodine receptor based on coarse-grained structural and dynamic modeling. Proteins 2015; 83:2307-18. [DOI: 10.1002/prot.24951] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Revised: 10/09/2015] [Accepted: 10/14/2015] [Indexed: 11/07/2022]
Affiliation(s)
- Wenjun Zheng
- Department of Physics; State University of New York at Buffalo; Buffalo New York 14260
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27
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Zheng W, Glenn P. Probing the folded state and mechanical unfolding pathways of T4 lysozyme using all-atom and coarse-grained molecular simulation. J Chem Phys 2015; 142:035101. [PMID: 25612731 DOI: 10.1063/1.4905606] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The Bacteriophage T4 Lysozyme (T4L) is a prototype modular protein comprised of an N-terminal and a C-domain domain, which was extensively studied to understand the folding/unfolding mechanism of modular proteins. To offer detailed structural and dynamic insights to the folded-state stability and the mechanical unfolding behaviors of T4L, we have performed extensive equilibrium and steered molecular dynamics simulations of both the wild-type (WT) and a circular permutation (CP) variant of T4L using all-atom and coarse-grained force fields. Our all-atom and coarse-grained simulations of the folded state have consistently found greater stability of the C-domain than the N-domain in isolation, which is in agreement with past thermostatic studies of T4L. While the all-atom simulation cannot fully explain the mechanical unfolding behaviors of the WT and the CP variant observed in an optical tweezers study, the coarse-grained simulations based on the Go model or a modified elastic network model (mENM) are in qualitative agreement with the experimental finding of greater unfolding cooperativity in the WT than the CP variant. Interestingly, the two coarse-grained models predict different structural mechanisms for the observed change in cooperativity between the WT and the CP variant--while the Go model predicts minor modification of the unfolding pathways by circular permutation (i.e., preserving the general order that the N-domain unfolds before the C-domain), the mENM predicts a dramatic change in unfolding pathways (e.g., different order of N/C-domain unfolding in the WT and the CP variant). Based on our simulations, we have analyzed the limitations of and the key differences between these models and offered testable predictions for future experiments to resolve the structural mechanism for cooperative folding/unfolding of T4L.
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Affiliation(s)
- Wenjun Zheng
- Department of Physics, University at Buffalo, Buffalo, New York 14260, USA
| | - Paul Glenn
- Department of Physics, University at Buffalo, Buffalo, New York 14260, USA
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28
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Chakraborty S, Zheng W. Decrypting the structural, dynamic, and energetic basis of a monomeric kinesin interacting with a tubulin dimer in three ATPase states by all-atom molecular dynamics simulation. Biochemistry 2015; 54:859-69. [PMID: 25537000 DOI: 10.1021/bi501056h] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
We have employed molecular dynamics (MD) simulation to investigate, with atomic details, the structural dynamics and energetics of three major ATPase states (ADP, APO, and ATP state) of a human kinesin-1 monomer in complex with a tubulin dimer. Starting from a recently solved crystal structure of ATP-like kinesin-tubulin complex by the Knossow lab, we have used flexible fitting of cryo-electron-microscopy maps to construct new structural models of the kinesin-tubulin complex in APO and ATP state, and then conducted extensive MD simulations (total 400 ns for each state), followed by flexibility analysis, principal component analysis, hydrogen bond analysis, and binding free energy analysis. Our modeling and simulation have revealed key nucleotide-dependent changes in the structure and flexibility of the nucleotide-binding pocket (featuring a highly flexible and open switch I in APO state) and the tubulin-binding site, and allosterically coupled motions driving the APO to ATP transition. In addition, our binding free energy analysis has identified a set of key residues involved in kinesin-tubulin binding. On the basis of our simulation, we have attempted to address several outstanding issues in kinesin study, including the possible roles of β-sheet twist and neck linker docking in regulating nucleotide release and binding, the structural mechanism of ADP release, and possible extension and shortening of α4 helix during the ATPase cycle. This study has provided a comprehensive structural and dynamic picture of kinesin's major ATPase states, and offered promising targets for future mutational and functional studies to investigate the molecular mechanism of kinesin motors.
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Affiliation(s)
- Srirupa Chakraborty
- Physics Department, University at Buffalo , Buffalo, New York 14260, United States
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29
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López-Blanco JR, Chacón P. Structural modeling from electron microscopy data. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2014. [DOI: 10.1002/wcms.1199] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- José Ramón López-Blanco
- Department of Biological Physical Chemistry; Rocasolano Physical Chemistry Institute, CSIC; Madrid Spain
| | - Pablo Chacón
- Department of Biological Physical Chemistry; Rocasolano Physical Chemistry Institute, CSIC; Madrid Spain
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30
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Heinrich F, Lösche M. Zooming in on disordered systems: neutron reflection studies of proteins associated with fluid membranes. BIOCHIMICA ET BIOPHYSICA ACTA 2014; 1838:2341-9. [PMID: 24674984 PMCID: PMC4082750 DOI: 10.1016/j.bbamem.2014.03.007] [Citation(s) in RCA: 76] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2013] [Revised: 03/13/2014] [Accepted: 03/17/2014] [Indexed: 11/23/2022]
Abstract
Neutron reflectometry (NR) is an emerging experimental technique for the structural characterization of proteins interacting with fluid bilayer membranes under conditions that mimic closely the cellular environment. Thus, cellular processes can be emulated in artificial systems and their molecular basis studied by adding cellular components one at a time in a well-controlled environment while the resulting structures, or structural changes in response to external cues, are monitored with neutron reflection. In recent years, sample environments, data collection strategies and data analysis were continuously refined. The combination of these improvements increases the information which can be obtained from NR to an extent that enables structural characterization of protein-membrane complexes at a length scale that exceeds the resolution of the measurement by far. Ultimately, the combination of NR with molecular dynamics (MD) simulations can be used to cross-validate the results of the two techniques and provide atomic-scale structural models. This review discusses these developments in detail and demonstrates how they provide new windows into relevant biomedical problems. This article is part of a Special Issue entitled: Interfacially Active Peptides and Proteins. Guest Editors: William C. Wimley and Kalina Hristova.
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Affiliation(s)
- Frank Heinrich
- Physics Department, Carnegie Mellon University, Pittsburgh, PA, U.S.A.; NIST Center for Neutron Research, Gaithersburg, MD, U.S.A
| | - Mathias Lösche
- Physics Department, Carnegie Mellon University, Pittsburgh, PA, U.S.A.; NIST Center for Neutron Research, Gaithersburg, MD, U.S.A..
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31
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Zheng W, Tekpinar M. High-resolution modeling of protein structures based on flexible fitting of low-resolution structural data. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2014; 96:267-84. [PMID: 25443961 DOI: 10.1016/bs.apcsb.2014.06.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/09/2022]
Abstract
To circumvent the difficulty of directly solving high-resolution biomolecular structures, low-resolution structural data from Cryo-electron microscopy (EM) and small angle solution X-ray scattering (SAXS) are increasingly used to explore multiple conformational states of biomolecular assemblies. One promising venue to obtain high-resolution structural models from low-resolution data is via data-constrained flexible fitting. To this end, we have developed a new method based on a coarse-grained Cα-only protein representation, and a modified form of the elastic network model (ENM) that allows large-scale conformational changes while maintaining the integrity of local structures including pseudo-bonds and secondary structures. Our method minimizes a pseudo-energy which linearly combines various terms of the modified ENM energy with an EM/SAXS-fitting score and a collision energy that penalizes steric collisions. Unlike some previous flexible fitting efforts using the lowest few normal modes, our method effectively utilizes all normal modes so that both global and local structural changes can be fully modeled with accuracy. This method is also highly efficient in computing time. We have demonstrated our method using adenylate kinase as a test case which undergoes a large open-to-close conformational change. The EM-fitting method is available at a web server (http://enm.lobos.nih.gov), and the SAXS-fitting method is available as a pre-compiled executable upon request.
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Affiliation(s)
- Wenjun Zheng
- Department of Physics, University at Buffalo, Buffalo, New York, USA.
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32
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Peng J, Zhang Z. Simulating Large-Scale Conformational Changes of Proteins by Accelerating Collective Motions Obtained from Principal Component Analysis. J Chem Theory Comput 2014; 10:3449-58. [DOI: 10.1021/ct5000988] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Junhui Peng
- Hefei National Laboratory
for Physical Science at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China
| | - Zhiyong Zhang
- Hefei National Laboratory
for Physical Science at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China
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33
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Bastolla U. Computing protein dynamics from protein structure with elastic network models. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2014. [DOI: 10.1002/wcms.1186] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Ugo Bastolla
- Centro de Biologa Molecular Severo Ochoa (CSIC‐UAM)Universidad Autónoma de MadridMadridSpain
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34
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Zheng W. All-atom and coarse-grained simulations of the forced unfolding pathways of the SNARE complex. Proteins 2014; 82:1376-86. [DOI: 10.1002/prot.24505] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2013] [Revised: 12/11/2013] [Accepted: 01/06/2014] [Indexed: 01/03/2023]
Affiliation(s)
- Wenjun Zheng
- Department of Physics; University at Buffalo, State University of New York; New York
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35
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Volkmann N. The joys and perils of flexible fitting. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2014; 805:137-55. [PMID: 24446360 DOI: 10.1007/978-3-319-02970-2_6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
While performing their functions, biological macromolecules often form large, dynamically changing macromolecular assemblies. Only a relatively small number of such assemblies have been accessible to the atomic-resolution techniques X-ray crystallography and NMR. Electron microscopy in conjunction with image reconstruction has become the preferred alternative for revealing the structures of such macromolecular complexes. However, for most assemblies the achievable resolution is too low to allow accurate atomic modeling directly from the data. Yet, useful models often can be obtained by fitting atomic models of individual components into a low-resolution reconstruction of the entire assembly. Several algorithms for achieving optimal fits in this context were developed recently, many allowing considerable degrees of flexibility to account for binding-induced conformational changes of the assembly components. This chapter describes the advantages and potential pitfalls of these methods and puts them into perspective with alternative approaches such as iterative modular fitting of rigid-body domains.
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Affiliation(s)
- Niels Volkmann
- Bioinformatics and Systems Biology Program, Sanford-Burnham Medical Research Institute, 10901 N Torrey Pines Rd, La Jolla, CA, 92037, USA,
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36
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iMODFIT: efficient and robust flexible fitting based on vibrational analysis in internal coordinates. J Struct Biol 2013; 184:261-70. [PMID: 23999189 DOI: 10.1016/j.jsb.2013.08.010] [Citation(s) in RCA: 127] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2013] [Revised: 08/20/2013] [Accepted: 08/22/2013] [Indexed: 12/31/2022]
Abstract
Here, we employed the collective motions extracted from Normal Mode Analysis (NMA) in internal coordinates (torsional space) for the flexible fitting of atomic-resolution structures into electron microscopy (EM) density maps. The proposed methodology was validated using a benchmark of simulated cases, highlighting its robustness over the full range of EM resolutions and even over coarse-grained representations. A systematic comparison with other methods further showcased the advantages of this proposed methodology, especially at medium to lower resolutions. Using this method, computational costs and potential overfitting problems are naturally reduced by constraining the search in low-frequency NMA space, where covalent geometry is implicitly maintained. This method also effectively captures the macromolecular changes of a representative set of experimental test cases. We believe that this novel approach will extend the currently available EM hybrid methods to the atomic-level interpretation of large conformational changes and their functional implications.
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37
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Wu X, Subramaniam S, Case DA, Wu KW, Brooks BR. Targeted conformational search with map-restrained self-guided Langevin dynamics: application to flexible fitting into electron microscopic density maps. J Struct Biol 2013; 183:429-440. [PMID: 23876978 DOI: 10.1016/j.jsb.2013.07.006] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2013] [Revised: 07/11/2013] [Accepted: 07/12/2013] [Indexed: 11/30/2022]
Abstract
We present a map-restrained self-guided Langevin dynamics (MapSGLD) simulation method for efficient targeted conformational search. The targeted conformational search represents simulations under restraints defined by experimental observations and/or by user specified structural requirements. Through map-restraints, this method provides an efficient way to maintain substructures and to set structure targets during conformational searching. With an enhanced conformational searching ability of self-guided Langevin dynamics, this approach is suitable for simulating large-scale conformational changes, such as the formation of macromolecular assemblies and transitions between different conformational states. Using several examples, we illustrate the application of this method in flexible fitting of atomic structures into density maps derived from cryo-electron microscopy.
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Affiliation(s)
- Xiongwu Wu
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD 20892, USA.
| | - Sriram Subramaniam
- Laboratory of Cell Biology, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892, USA
| | - David A Case
- BioMaPS Institute and Dept. of Chemistry & Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA
| | - Katherine W Wu
- Thomas Jefferson High School for Science and Technology, Alexandria, VA 22312, USA
| | - Bernard R Brooks
- Laboratory of Computational Biology, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD 20892, USA
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BAJAJ CHANDRAJIT, BAUER BENEDIKT, BETTADAPURA RADHAKRISHNA, VOLLRATH ANTJE. NONUNIFORM FOURIER TRANSFORMS FOR RIGID-BODY AND MULTI-DIMENSIONAL ROTATIONAL CORRELATIONS. SIAM JOURNAL ON SCIENTIFIC COMPUTING : A PUBLICATION OF THE SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS 2013; 35:10.1137/120892386. [PMID: 24379643 PMCID: PMC3874283 DOI: 10.1137/120892386] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
The task of evaluating correlations is central to computational structural biology. The rigid-body correlation problem seeks the rigid-body transformation (R, t), R ∈ SO(3), t ∈ ℝ3 that maximizes the correlation between a pair of input scalar-valued functions representing molecular structures. Exhaustive solutions to the rigid-body correlation problem take advantage of the fast Fourier transform to achieve a speedup either with respect to the sought translation or rotation. We present PFcorr, a new exhaustive solution, based on the non-equispaced SO(3) Fourier transform, to the rigid-body correlation problem; unlike previous solutions, ours achieves a combination of translational and rotational speedups without requiring equispaced grids. PFcorr can be straightforwardly applied to a variety of problems in protein structure prediction and refinement that involve correlations under rigid-body motions of the protein. Additionally, we show how it applies, along with an appropriate flexibility model, to analogs of the above problems in which the flexibility of the protein is relevant.
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Affiliation(s)
- CHANDRAJIT BAJAJ
- Computational Visualization Center, Department of Computer Sciences and The Institute of Computational Engineering and Sciences, The University of Texas at Austin, 1 University Station C0200, Austin, Texas 78712, USA
| | - BENEDIKT BAUER
- Max Planck Institute for Evolutionary Biology. Plön, Germany
| | - RADHAKRISHNA BETTADAPURA
- Computational Visualization Center, Department of Mechanical Engineering, The University of Texas at Austin, 1 University Station C0200, Austin, Texas 78712, USA
| | - ANTJE VOLLRATH
- Institute of Computational Mathematics, TU Braunschweig, Pockelsstr 14, 38106 Braunschweig, Germany
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39
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Esquivel-Rodríguez J, Kihara D. Computational methods for constructing protein structure models from 3D electron microscopy maps. J Struct Biol 2013; 184:93-102. [PMID: 23796504 DOI: 10.1016/j.jsb.2013.06.008] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2012] [Revised: 06/11/2013] [Accepted: 06/13/2013] [Indexed: 12/31/2022]
Abstract
Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solved at high resolutions close to 3Å. Computational methods play a key role in interpreting EM data. Among many computational procedures applied to an EM map to obtain protein structure information, in this article we focus on reviewing computational methods that model protein three-dimensional (3D) structures from a 3D EM density map that is constructed from two-dimensional (2D) maps. The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map. A list of available computational tools is also provided.
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Affiliation(s)
- Juan Esquivel-Rodríguez
- Department of Computer Science, College of Science, Purdue University, West Lafayette, IN 47907, USA
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40
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Consensus among multiple approaches as a reliability measure for flexible fitting into cryo-EM data. J Struct Biol 2013; 182:67-77. [PMID: 23416197 DOI: 10.1016/j.jsb.2013.02.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2012] [Revised: 01/29/2013] [Accepted: 02/01/2013] [Indexed: 12/14/2022]
Abstract
Cryo-electron microscopy (cryo-EM) can provide low-resolution density maps of large macromolecular assemblies. As the number of structures deposited in the Protein Data Bank by fitting a high-resolution structure into a low-resolution cryo-EM map is increasing, there is a need to revise the protocols and improve the measures for fitting. A recent study suggested using a combination of multiple automated flexible fitting approaches to improve the interpretation of cryo-EM data. The current work further explores the use of multiple approaches by validating this "consensus" fitting approach and deriving a local reliability measure. Here four different flexible fitting approaches are applied for fitting an initial structure into a simulated density map of known target structure from a dataset of proteins. It is found that the models produced from different approaches often have a consensus in conformation and are also near to the target structure, whereas cases not showing consensus are away from the target. A high correlation is also observed between the RMSF profiles calculated with respect to the average and the target structures, which indicates that the relation between consensus and accuracy can also be extended to a per-residue level. Therefore, the RMSF among the fitted models is proposed as a local reliability measure, which can be used to assess the reliability of the fit at specific regions. Hence, we encourage the community to use consensus flexible fitting with different methods to report on local reliability of the resulting models and improve the interpretation of cryo-EM data.
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41
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Structure-based simulations of the translocation mechanism of the hepatitis C virus NS3 helicase along single-stranded nucleic acid. Biophys J 2013; 103:1343-53. [PMID: 22995507 DOI: 10.1016/j.bpj.2012.08.026] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2012] [Revised: 08/01/2012] [Accepted: 08/06/2012] [Indexed: 01/14/2023] Open
Abstract
The NS3 helicase of Hepatitis C virus is an ATP-fueled molecular motor that can translocate along single-stranded (ss) nucleic acid, and unwind double-stranded nucleic acids. It makes a promising antiviral target and an important prototype system for helicase research. Despite recent progress, the detailed mechanism of NS3 helicase remains unknown. In this study, we have combined coarse-grained (CG) and atomistic simulations to probe the translocation mechanism of NS3 helicase along ssDNA. At the residue level of detail, our CG simulations have captured functionally important interdomain motions of NS3 helicase and reproduced single-base translocation of NS3 helicase along ssDNA in the 3'-5' direction, which is in good agreement with experimental data and the inchworm model. By combining the CG simulations with residue-specific perturbations to protein-DNA interactions, we have identified a number of key residues important to the translocation machinery that agree with previous structural and mutational studies. Additionally, our atomistic simulations with targeted molecular dynamics have corroborated the findings of CG simulations and further revealed key protein-DNA hydrogen bonds that break/form during the transitions. This study offers, to our knowledge, the most detailed and realistic simulations of translocation mechanism of NS3 helicase. The simulation protocol established in this study will be useful for designing inhibitors that target the translocation machinery of NS3 helicase, and for simulations of a variety of nucleic-acid-based molecular motors.
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42
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Tekpinar M, Zheng W. Coarse-grained and all-atom modeling of structural states and transitions in hemoglobin. Proteins 2012; 81:240-52. [PMID: 22987685 DOI: 10.1002/prot.24180] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2012] [Revised: 08/27/2012] [Accepted: 09/10/2012] [Indexed: 11/08/2022]
Abstract
Hemoglobin (Hb), an oxygen-binding protein composed of four subunits (α1, α2, β1, and β2), is a well-known example of allosteric proteins that are capable of cooperative ligand binding. Despite decades of studies, the structural basis of its cooperativity remains controversial. In this study, we have integrated coarse-grained (CG) modeling, all-atom simulation, and structural data from X-ray crystallography and wide-angle X-ray scattering (WAXS), aiming to probe dynamic properties of the two structural states of Hb (T and R state) and the transitions between them. First, by analyzing the WAXS data of unliganded and liganded Hb, we have found that the structural ensemble of T or R state is dominated by one crystal structure of Hb with small contributions from other crystal structures of Hb. Second, we have used normal mode analysis to identify two distinct quaternary rotations between the α1β1 and α2β2 dimer, which drive the transitions between T and R state. We have also identified the hot-spot residues whose mutations are predicted to greatly change these quaternary motions. Third, we have generated a CG transition pathway between T and R state, which predicts a clear order of quaternary and tertiary changes involving α and β subunits in Hb. Fourth, we have used the accelerated molecular dynamics to perform an all-atom simulation starting from the T state of Hb, and we have observed a transition toward the R state of Hb. Further analysis of crystal structural data and the all-atom simulation trajectory has corroborated the order of quaternary and tertiary changes predicted by CG modeling.
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Affiliation(s)
- Mustafa Tekpinar
- Physics Department, University at Buffalo, Buffalo, New York 14260, USA
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43
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Wang Z, Schröder GF. Real-space refinement with DireX: from global fitting to side-chain improvements. Biopolymers 2012; 97:687-97. [PMID: 22696405 DOI: 10.1002/bip.22046] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Single-particle cryo-electron microscopy (cryo-EM) has become an important tool to determine the structure of large biomolecules and assemblies thereof. However, the achievable resolution varies considerably over a wide range of about 3.5-20 Å. The interpretation of these intermediate- to low-resolution density maps in terms of atomic models is a big challenge and an area of active research. Here, we present our real-space structure refinement program DireX, which was developed primarily for cryo-EM-derived density maps. The basic principle and its main features are described. DireX employs Deformable Elastic Network (DEN) restraints to reduce overfitting by decreasing the effective number of degrees of freedom used in the refinement. Missing or reduced density due to flexible parts of the protein can lead to artifacts in the structure refinement, which is addressed through the concept of restrained grouped occupancy refinement. Furthermore, we describe the performance of DireX in the 2010 Cryo-EM Modeling Challenge, where we chose six density maps of four different proteins provided by the Modeling Challenge exemplifying typical refinement results at a large resolution range from 3 to 23 Å.
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Affiliation(s)
- Zhe Wang
- Institute of Complex Systems, Forschungszentrum Jülich, Jülich, Germany
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44
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Zhang Q, Bettadapura R, Bajaj C. Macromolecular structure modeling from 3D EM using VolRover 2.0. Biopolymers 2012; 97:709-31. [PMID: 22696407 DOI: 10.1002/bip.22052] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
We review tools for structure identification and model-based refinement from three-dimensional electron microscopy implemented in our in-house software package, VOLROVER 2.0. For viral density maps with icosahedral symmetry, we segment the capsid, polymeric, and monomeric subunits using techniques based on automatic symmetry detection and multidomain fast marching. For large biomolecules without symmetry information, we again use our multidomain fast-marching method with manual or fit-based multiseeding to segment meaningful substructures. In either case, we subject the resulting segmented subunit to secondary structure detection when the EM resolution is sufficiently high, and rigid-body structure fitting when the corresponding X-ray structure is available. Secondary structure elements are identified by three techniques: our earlier volume-based and boundary-based skeletonization methods as well as a new method, currently in development, based on solving the grassfire flow equation. For rigid-body fitting, we adapt our earlier fast Fourier-based correlation scheme F2Dock. Our reported segmentation, secondary structure elements identification, and rigid-body fitting techniques, implemented in VOLROVER 2.0 are applied to the PSB 2011 cryo-EM modeling challenge data, and our results are briefly compared to similar results submitted from other research groups. The comparisons show that our techniques are equally capable of segmenting relatively accurate subunits from a viral or protein assembly, and that high segmentation quality leads in turn to higher-quality results of secondary structure elements identification and correlation-based rigid-body fitting. © 2012 Wiley Periodicals, Inc. Biopolymers 97: 709-731, 2012.
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Affiliation(s)
- Qin Zhang
- Institute for Computational Engineering and Sciences, The University of Texas, Austin, TX 78712, USA
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45
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Lander GC, Saibil HR, Nogales E. Go hybrid: EM, crystallography, and beyond. Curr Opin Struct Biol 2012; 22:627-35. [PMID: 22835744 DOI: 10.1016/j.sbi.2012.07.006] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2012] [Revised: 06/21/2012] [Accepted: 07/09/2012] [Indexed: 01/30/2023]
Abstract
A mechanistic understanding of the molecular transactions that govern cellular function requires knowledge of the dynamic organization of the macromolecular machines involved in these processes. Structural biologists employ a variety of biophysical methods to study large macromolecular complexes, but no single technique is likely to provide a complete description of the structure-function relationship of all the constituent components. Since structural studies generally only provide snapshots of these dynamic machines as they accomplish their molecular functions, combining data from many methodologies is crucial to our understanding of molecular function.
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Affiliation(s)
- Gabriel C Lander
- Life Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
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46
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Li M, Zheng W. All-atom structural investigation of kinesin-microtubule complex constrained by high-quality cryo-electron-microscopy maps. Biochemistry 2012; 51:5022-32. [PMID: 22650362 DOI: 10.1021/bi300362a] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In this study, we have performed a comprehensive structural investigation of three major biochemical states of a kinesin complexed with microtubule under the constraint of high-quality cryo-electron-microscopy (EM) maps. In addition to the ADP and ATP state which were captured by X-ray crystallography, we have also modeled the nucleotide-free or APO state for which no crystal structure is available. We have combined flexible fitting of EM maps with regular molecular dynamics simulations, hydrogen-bond analysis, and free energy calculation. Our APO-state models feature a subdomain rotation involving loop L2 and α6 helix of kinesin, and local structural changes in active site similar to a related motor protein, myosin. We have identified a list of hydrogen bonds involving key residues in the active site and the binding interface between kinesin and microtubule. Some of these hydrogen bonds may play an important role in coupling microtubule binding to ATPase activities in kinesin. We have validated our models by calculating the binding free energy between kinesin and microtubule, which quantitatively accounts for the observation of strong binding in the APO and ATP state and weak binding in the ADP state. This study will offer promising targets for future mutational and functional studies to investigate the mechanism of kinesin motors.
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Affiliation(s)
- Minghui Li
- Physics Department, University at Buffalo, Buffalo, NY 14260, USA
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47
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Esquivel-Rodríguez J, Kihara D. Fitting multimeric protein complexes into electron microscopy maps using 3D Zernike descriptors. J Phys Chem B 2012; 116:6854-61. [PMID: 22417139 PMCID: PMC3376205 DOI: 10.1021/jp212612t] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A novel computational method for fitting high-resolution structures of multiple proteins into a cryoelectron microscopy map is presented. The method named EMLZerD generates a pool of candidate multiple protein docking conformations of component proteins, which are later compared with a provided electron microscopy (EM) density map to select the ones that fit well into the EM map. The comparison of docking conformations and the EM map is performed using the 3D Zernike descriptor (3DZD), a mathematical series expansion of three-dimensional functions. The 3DZD provides a unified representation of the surface shape of multimeric protein complex models and EM maps, which allows a convenient, fast quantitative comparison of the three-dimensional structural data. Out of 19 multimeric complexes tested, near native complex structures with a root-mean-square deviation of less than 2.5 Å were obtained for 14 cases while medium range resolution structures with correct topology were computed for the additional 5 cases.
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Affiliation(s)
| | - Daisuke Kihara
- Department of Biological Sciences, Purdue University, West Lafayette, IN, 47907, USA
- Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA
- Markey Center for Structural Biology, Purdue University, West Lafayette, IN, 47907, USA
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48
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Leioatts N, Romo TD, Grossfield A. Elastic Network Models are Robust to Variations in Formalism. J Chem Theory Comput 2012; 8:2424-2434. [PMID: 22924033 DOI: 10.1021/ct3000316] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Understanding the functions of biomolecules requires insight not only from structures, but from dynamics as well. Often, the most interesting processes occur on time scales too slow for exploration by conventional molecular dynamics (MD) simulations. For this reason, alternative computational methods such as elastic network models (ENMs) have become increasingly popular. These simple, coarse-grained models represent molecules as beads connected by harmonic springs; the system's motions are solved analytically by normal mode analysis. In the past few years, many different formalisms for performing ENM calculations have emerged, and several have been optimized using all-atom MD simulations. In contrast to other studies, we have compared the various formalisms in a systematic, quantitative way. In this study, we optimize many ENM functional forms using a uniform dataset containing only long (> 1 μs) all-atom MD simulations. Our results show that all models once optimized produce spring constants for immediate neighboring residues that are orders of magnitude stiffer than more distal contacts. In addition, the statistical significance of ENM performance varied with model resolution. We also show that fitting long trajectories does not improve ENM performance due to a problem inherent in all network models tested: they underestimate the relative importance of the most concerted motions. Finally, we characterize ENMs' resilience by tessellating the parameter space to show that broad ranges of parameters produce similar quality predictions. Taken together our data reveals that choice of spring function and parameters are not vital to performance of a network model and that simple parameters can by derived "by hand" when no data is available for fitting, thus illustrating the robustness of these models.
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Affiliation(s)
- Nicholas Leioatts
- Department of Biochemistry & Biophysics, University of Rochester Medical Center, Rochester, NY 14642, USA
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49
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Trinh MH, Odorico M, Pique ME, Teulon JM, Roberts VA, Ten Eyck LF, Getzoff ED, Parot P, Chen SWW, Pellequer JL. Computational reconstruction of multidomain proteins using atomic force microscopy data. Structure 2012; 20:113-20. [PMID: 22244760 DOI: 10.1016/j.str.2011.10.023] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2011] [Revised: 10/05/2011] [Accepted: 10/10/2011] [Indexed: 01/10/2023]
Abstract
Classical structural biology techniques face a great challenge to determine the structure at the atomic level of large and flexible macromolecules. We present a novel methodology that combines high-resolution AFM topographic images with atomic coordinates of proteins to assemble very large macromolecules or particles. Our method uses a two-step protocol: atomic coordinates of individual domains are docked beneath the molecular surface of the large macromolecule, and then each domain is assembled using a combinatorial search. The protocol was validated on three test cases: a simulated system of antibody structures; and two experimentally based test cases: Tobacco mosaic virus, a rod-shaped virus; and Aquaporin Z, a bacterial membrane protein. We have shown that AFM-intermediate resolution topography and partial surface data are useful constraints for building macromolecular assemblies. The protocol is applicable to multicomponent structures connected in the polypeptide chain or as disjoint molecules. The approach effectively increases the resolution of AFM beyond topographical information down to atomic-detail structures.
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Affiliation(s)
- Minh-Hieu Trinh
- CEA, iBEB, Department of Biochemistry and Nuclear Toxicology, F-30207 Bagnols sur Cèze, France
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50
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Finding rigid bodies in protein structures: Application to flexible fitting into cryoEM maps. J Struct Biol 2012; 177:520-31. [DOI: 10.1016/j.jsb.2011.10.011] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2011] [Revised: 10/22/2011] [Accepted: 10/27/2011] [Indexed: 11/18/2022]
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